12-17, 2022

Business Assignment代寫范例-投資組合理論概述。本文是一篇留學生商業管理方向assignment寫作參考，主要內容是講述“投資組合”一詞可定義為：；決定個人未來前景的所有決定”。投資組合可以包括許多類型的資產，如廠房、房地產、房地產和金融資產。投資組合理論提出了理性和謹慎的投資者應該如何利用其盡職調查使投資多樣化以優化投資組合，以及與風險較小的資產相比，風險資產應該如何定價。幾十年來，人們一直在投資不同的資產類別，但他們意識到風險的重要性及其負面影響，如果不加以有效處理。每個投資者都有自己的風險承受能力，投資者的風險承受力取決于其承受能力。投資組合理論是隨著時間的推移而產生的，目的是有效地衡量風險，以及如何通過資產多樣化來降低風險。下面就請參考這篇assignment寫作范文。

**Introduction 引言**

The word “Portfolio” can be defined as; the totality of decisions determining an individual’s future prospects” (Sharpe, 1970). Portfolio can consist of many types of assets such as plant, property, real and financial assets (P.A Bowen, 1984). Portfolio theories propose how rational and prudent investors should use their due diligence to diversify their investments to optimize their portfolios, and how a risky asset should be priced as compared to less risky asset. People have been investing in the different assets class since decades but then they realize the importance of risk and its negative implications, if not treated effectively. Every investor has his own tolerance of risk and investor’s defines it in his ability of taking it. The portfolio theories have been derived over time in order to effectively measure the risk and how it can be reduced by diversify in their asset.

**Assignment 1: “The Legacy of Modern Portfolio Theory”“現代投資組合理論的遺產”**

This assignment covers the highlights of modern portfolio theory, describing how risk and its effects are measured and how planning and asset allocation can help you do something about it. Modern portfolio theory is the theoretical conflicting of conventional stock picking. It is being put forward by the economists, who try to understand the phenomena of the market as a whole, instead of business analysts, who look for individual investment opportunities. Investments are explained statistically, as how much investor expected long-term return rate and their expected short-term volatility. It measures how much expected return can deviate much worse than average an investment’s bad years are likely to be. The goal of the theory is to identify your adequate level of risk tolerance, and then to come up with a portfolio with the maximum expected return for that level of standard deviation (risk).

本文涵蓋了現代投資組合理論的重點，描述了如何衡量風險及其影響，以及規劃和資產配置如何幫助您解決這些問題?，F代投資組合理論是傳統股票選擇的理論沖突。這是由經濟學家提出的，他們試圖理解整個市場的現象，而不是商業分析師，他們尋找個人投資機會。對投資進行統計解釋，包括投資者預期的長期回報率和預期的短期波動率。它衡量的是預期回報的偏離程度，遠比投資糟糕年份的平均水平差。該理論的目標是確定您的風險承受能力水平，然后針對該標準差（風險）水平提出具有最大預期回報的投資組合。

The portfolio it assumes that the investment universe consists only of two market securities, the risk free asset and risky assets. But the actual investment universe is much broader than that being put forward. The optimal level of investment is to invest on efficient frontier but doing this would mean to calculate the millions of covariance among the securities. This calculation could make the life of analyst as difficult as one could have ever imagined. To think practically, it’s better to put portfolio theory to work means investing in a limited number of index securities rather than a huge number of individual stocks and bonds. Index investing is the point the where portfolio theory starts to rely on the efficient market hypothesis. When you buy an index based portfolio strategy you’re allocating your money the same way the whole market is – which is a high-quality thing if you believe the market has a plan and it is efficient. This is why portfolio theory is one of the branches of economics rather than finance: instead of only studying financial statements and different financial ratios, you study the aggregate behavior of investors, some of whom seemingly have studied financial statements so that market valuations will reflect their due diligence and prudence.

它假設投資領域僅由兩種市場證券組成，即無風險資產和風險資產。但實際的投資范圍比提出的要廣得多。最佳投資水平是投資于有效前沿，但這樣做意味著計算證券之間的數百萬協方差。這種計算可能會使分析師的生活變得像人們想象的那樣困難。從實際情況來看，將投資組合理論付諸實施意味著投資于數量有限的指數證券，而不是大量的股票和債券。指數投資是投資組合理論開始依賴于有效市場假說的一點。當你購買基于指數的投資組合策略時，你的資金分配方式與整個市場相同——如果你相信市場有計劃且效率高，那么這是一件高質量的事情。這就是為什么投資組合理論是經濟學而不是金融學的分支之一：你研究的不是財務報表和不同的財務比率，而是投資者的總體行為，其中一些人似乎研究過財務報表，以便市場估值反映出他們的盡職調查和謹慎。

**Assignment 2: “Theory of portfolio and risk based on incremental entropy”“基于增量熵的投資組合和風險理論”**

The assignment has used incremental entropy to optimize the portfolios. This novel portfolio theory has been based on incremental entropy that carries on some facet of Markowitz’s (1959, 1991) theory, but it highlights that the incremental speed of capital is a more objective criterion for assessing portfolios. The performance of the portfolio just cannot be justified with the returns because we have to keep in mind the risk of achieving those returns. Given the probability forecasts of returns, we can obtain the best possible investment ratio. Combining the new portfolio theory and the general theory of information, we can approach a meaning-explicit measure, which represents the increment of capital-increasing speed after information is provided. The assignment has used example to make it more clear that as we try to become rich within days there involve high risk of even losing those money which we at-least own at present. The ineffective investment is like a coin toss either you have all the money in your pocket or you end having nothing in your pocket. The same being very risk averse would not help you become rich. You there has to be a balance in selecting the portfolio and this assignment explain the optimal investment ratio. (pg 1)

本文使用了增量熵來優化投資組合。這一新穎的投資組合理論以增量熵為基礎，它繼承了Markowitz理論的某些方面，但它強調資本的增量速度是評估投資組合的更客觀的標準。投資組合的表現不能用回報來證明，因為我們必須牢記實現這些回報的風險。給定回報的概率預測，我們可以獲得最佳可能的投資比率。結合新的投資組合理論和信息的一般理論，我們可以找到一個意義明確的度量，它表示信息提供后資本增長速度的增量。這篇文章用了一個例子來更清楚地說明，當我們試圖在幾天內變得富有的時候，我們甚至有很高的風險失去那些我們目前至少擁有的錢。無效的投資就像擲硬幣，要么你口袋里有錢，要么你兜里一無所有。同樣，非常厭惡風險也無助于你致富。你必須在選擇投資組合時保持平衡，本文將解釋最佳投資比例。

Markowitz explains us that an efficient portfolio is either a portfolio that offers the maximum expected return for a given level of risk, or one with the minimum level of risk for a given expected return. There is no objective criterion to define the maximum effectiveness of a portfolio given the expected return and risk level and different expects have different view about it. The Markowitz’s efficient portfolio tells us about the indifference curve of the investor and about the market portfolio. It is not the portfolio which we need for the fastest increment of capital. So, this assignment has derived a new mathematical model.

Markowitz向我們解釋說，有效的投資組合要么是在給定風險水平下提供最大預期回報的投資組合，要么是在特定預期回報下具有最小風險水平的投資組合?？紤]到預期回報和風險水平，沒有客觀標準來定義投資組合的最大有效性，不同的預期對此有不同的看法。馬科維茨的有效投資組合告訴我們投資者的無差異曲線和市場投資組合。這不是我們需要的最快資本增長的投資組合。因此，本文導出了一個新的數學模型。

The model explains that when gain and loss are have equal chance of occurring, if the loss is up to 100 percent, one should not risk more than 50 percent of fund no matter how lofty the possible gain might be. This conclusion has a great importance and significant for risky investments, such as futures, options, etc. Most of the new investors of future markets lose all of their money very fast because the investment ratios are not well controlled and generally too large. we can obtain the optimal ratios of investments in different securities or assets when probability forecasts of returns are given.

該模型解釋說，當收益和損失發生的機會相等時，如果損失達到100%，則無論可能的收益有多高，都不應承擔超過50%的基金風險。這一結論對風險投資（如期貨、期權等）具有重要意義。大多數期貨市場的新投資者很快就失去了所有的資金，因為投資比率沒有得到很好的控制，而且通常太大。當給出收益的概率預測時，我們可以獲得不同證券或資產的最優投資比例。

Comparison with Markowitz’s theory 與馬科維茨理論的比較

The new theory supports Markowitz’s conclusions that investment risk can be reduced by effective portfolio, but there are some obvious differences: The new theory uses geometric mean return as the objective criterion for optimizing portfolio and gives some formulas for optimizing investment ratios; and . The new theory makes use of extent and possibility of gain and loss rather than expectation of return and standard deviation (risk) of the return to explain investment value.

新理論支持Markowitz的結論，即有效投資組合可以降低投資風險，但有一些明顯的區別：新理論使用幾何平均收益作為優化投資組合的客觀標準，并給出了一些優化投資比率的公式；新理論利用收益和損失的程度和可能性，而不是收益預期和收益標準差（風險）來解釋投資價值。

Assignment 3: “On the competitive theory and practice of portfolio selection”“關于投資組合選擇的競爭理論和實踐”

To select an optimal level of portfolio has always been a basic and fundamental problem in the field of computation finance. There are lots of securities are available including the cash and the basic online problem is to agree on a portfolio for the ith trading period based on the series of price for the scheduled i-1 trading period. There has been increasing interest but also mounting uncertainty relating to the value of competitive theory of online portfolio selection algorithms. Competitive analysis is based on the worst and most unexpected case scenarios and viewpoint; such a point of view is conflicting with the most widely used analysis and theories being adopted by the investors based on the statistical models and assumptions. Surprisingly in some of the initial experiments result shows that some algorithms which have enjoyed a highly regarded repute seems to outperform the historical sequence of data when seen in relation to competitive worst case scenarios. The emerging competitive theory and the algorithms are directly related to the studies in information theory and computational learning theory, in fact some of the algorithms have been the broken new ground and set new standards within the information and computational theory learning based communities. The one of the primary goal and objective of this paper is understand the extent to which competitive portfolio algorithms are in reality learning and are they really contributing to the welfare of the investor. In order to find out so they have used set of different strategies this can be adapted to data sequence. This is being presented in a mixture of both strong theoretical and experimental results. It has also been compared with the performance of existing and new algorithms and respects to standard series of the historical sequence data and it also present the experiments from other three data sequence. It is being concluded that there is huge potential for selecting portfolio through algorithms that are being derived from competitive force and as well as derived from the statistical properties of data.

選擇最優投資組合水平一直是計算金融領域的一個基本問題。有很多證券可用，包括現金，基本的在線問題是根據計劃的i-1交易期的系列價格，就第i個交易期的投資組合達成一致。人們對在線投資組合選擇算法的競爭理論的價值越來越感興趣，但也越來越不確定。競爭分析基于最壞和最意想不到的案例場景和觀點；這種觀點與投資者基于統計模型和假設所采用的最廣泛的分析和理論相沖突。令人驚訝的是，在一些最初的實驗中，結果顯示，當與競爭性最壞情況場景相關時，一些享有極高聲譽的算法似乎優于歷史數據序列。新興的競爭理論和算法與信息理論和計算學習理論的研究直接相關，事實上，其中一些算法已經在基于信息和計算理論學習的社區中開辟了新的領域并制定了新的標準。本文的主要目標之一是了解競爭性投資組合算法在現實學習中的應用程度，以及它們是否真正有助于投資者的福利。為了找出原因，他們使用了一組不同的策略，這可以根據數據序列進行調整。這是一個強有力的理論和實驗結果的混合物。它還與現有和新算法的性能進行了比較，并與標準系列的歷史序列數據進行了比較。人們得出的結論是，通過從競爭力以及從數據的統計特性中得出的算法來選擇投資組合具有巨大的潛力。

**Assignment 4: “International property Portfolio Strategies”“國際房地產投資組合策略”**

The assignment talks about the investment decisions regarding real estate, and try to put in the Markowitz mean variance formula to analyze the real estate market. They are not confined only to local real estate diversification but they are also including international diversification. Markowitz mean variance continuum and graph is useful in analyzing the efficient securities, and they help in the selection of an optimal portfolio on envelope curve taking into account the risk preferences of an investor. But when analysts try to incorporate real estate market to the Markowitz theory the major problems regarding liquidity, heterogeneity, indivisibility and information are faced by them which restrict them from further optimal analysis.

本文討論了房地產投資決策，并試圖運用Markowitz均值方差公式對房地產市場進行分析。它們不僅限于本地房地產多元化，還包括國際多元化。Markowitz均值-方差連續體和圖表在分析有效證券時非常有用，它們有助于在考慮投資者風險偏好的情況下選擇包絡曲線上的最優投資組合。但是，當分析師試圖將房地產市場納入Markowitz理論時，他們面臨的主要問題是流動性、異質性、不可分割性和信息，這些問題限制了他們進行進一步的優化分析。

Many investors have tried to support the theory to make a portfolio by considering property as asset like equity and bond investments; although there are a lot of differences among the characteristics of assets discussed above, but one can diversify its portfolio by investing in real assets, analysts argue. The discussion was dominated by the concept of international diversification of assets including real estate. To support the analysis in UK the (Sweeney , 1988-1989) work in cited most of the times, he came up with the famous model of real estate to come up with efficient diversification strategy, he used rental value of for different countries and came up with the model of risk return theory; after that a lot of analysts including: [Baum and Schofield (1991), Brühl and Lizieri (1994), Gordon (1991), Hartzell et al. (1993), Johnson (1993), Sweeney (1993), Vo(1993) and Wurtzebach (1990)], have come up with analysis to support international diversification; but the result was somehow was not justifying the inculcation of real estate to portfolio theory, because those assets were not correlated at all when inspected for the risk return behavior during last decade or so. This can be attributed to the failure of mean variance model to produce results, the main problems facing would be regarding data collection, technicalities, omitted categories, and ex post analysis.

許多投資者試圖通過將房地產視為資產（如股票和債券投資）來支持投資組合的理論；分析人士認為，盡管上述資產的特征有很多不同，但通過投資實物資產，可以實現投資組合的多樣化。討論主要是包括房地產在內的資產的國際多樣化概念。為了支持英國的分析，的工作在大多數時候被引用，他提出了著名的房地產模型，以提出有效的多元化策略，他使用了不同國家的租金價值，并提出了風險回報理論模型；之后，許多分析師，包括：[Baum和Schofield，Brühl和Lizieri，Gordon、Hartzell等人，Johnson、Sweeney和Vo以及Wurtzebach，都提出了支持國際多元化的分析；但其結果不知何故并不能證明將房地產引入投資組合理論是合理的，因為在過去十年左右的風險回報行為中，這些資產根本不相關。這可歸因于均值-方差模型未能產生結果，面臨的主要問題是數據收集、技術性、遺漏類別和事后分析。

This is almost irrational and impossible to find the most efficient way to diversify a portfolio by including real asset as a separate asset, because of area problems, different locality, pricing conditions, economic conditions, liquidity differences, and data collection problems. As real estate market is highly uncorrelated even within the industry so the data sets are very difficult to find for analysis because of lack of empirical data on this market.

由于地區問題、不同地區、定價條件、經濟條件、流動性差異和數據收集問題，這幾乎是不合理的，也不可能找到通過將真實資產作為單獨資產來實現投資組合多樣化的最有效方法。由于房地產市場即使在行業內也高度不相關，因此由于缺乏該市場的經驗數據，很難找到數據集進行分析。

**Assignment 5: “Different risk measures: different portfolio compositions?”“不同的風險度量：不同的投資組合組成？”**

Choosing the suitable portfolio of assets in which to invest is an essential component of fund management. A large percentage of portfolio selection decisions were based on a qualitative basis, however quantitative approaches to selection are increasingly being employed. Markowitz (1952) established a quantitative framework for asset selection into a portfolio that is now well known. The measure of risk used in portfolio optimization models is the variance. Variance calculates how much deviation could be expected from the set of portfolio. The alternative methods of risk have their own theoretical and practical advantages and it is atypical that they are not used widely by investors. One of the reason may be because of the difficulty and complexity of understanding such models and then practically implementing those models and to decide in which measure of risk is best and gives the most realistic and useful results. It is important to identify the common risk measure and without doing so any attempt to measure the risk would be useless exercise. In order to cope with this, another approach is considered that is to comparing the portfolio holdings produced by different risk measures, rather than the traditional risk return trade-off. It is than being observed that whether the risk measures used produce asset allocations that are essentially the same or very different. In order to probe this concern this study tested the proposition that different measures of risk produce minimum risk portfolios that are essentially the same in terms of asset allocations, using monthly data over the period January 1987 to December 2002. The results show that the optimal portfolio compositions formed by different risk measures vary quite noticeably from measure to measure. These finding are very useful and have a practical implication for the investors because it recommend that the choice of risk model depends entirely on the individual’s attitude to risk rather than any theoretical or practical advantages of one model over another. It has been concluded that different investors have they indifference curve different from other and some of them like to take more risk as compare to other who are happy at earning low but safe returns.

選擇合適的投資資產組合是基金管理的重要組成部分。很大比例的投資組合選擇決策是基于定性的，但越來越多地采用定量的選擇方法。Markowitz建立了一個量化框架，用于將資產選擇納入現在眾所周知的投資組合。投資組合優化模型中使用的風險度量是方差。方差計算投資組合的預期偏差。替代風險方法有其自身的理論和實踐優勢，投資者不廣泛使用這種方法是不典型的。其中一個原因可能是因為理解這些模型，然后實際實施這些模型，并決定哪種風險度量是最好的，并給出最現實和有用的結果，這是困難和復雜的。確定共同風險度量是很重要的，如果不這樣做，任何衡量風險的嘗試都是徒勞的。為了應對這一問題，考慮了另一種方法，即比較不同風險度量產生的投資組合持有量，而不是傳統的風險收益權衡。人們還觀察到，所使用的風險度量是否產生了本質上相同或非常不同的資產配置。為了探討這一問題，本研究使用1987年1月至2002年12月期間的月度數據，檢驗了不同風險度量產生的最小風險投資組合在資產配置方面基本相同的命題。結果表明，不同風險度量形成的最優投資組合在不同度量之間差異很大。這些發現非常有用，對投資者具有實際意義，因為它建議風險模型的選擇完全取決于個人對風險的態度，而不是一種模型相對于另一種模型的任何理論或實際優勢。已經得出的結論是，不同的投資者有著不同于其他投資者的冷漠曲線，其中一些人喜歡承擔更多的風險，而其他人則樂于獲得低但安全的回報。

**Conclusion 結論**

It is being concluded that risk is more of a subjective term and different analysts and investor measures and perceive it in their own way. In today’s word not even a single person can underestimate the importance of risk in selecting a security and emphasized is been given to diversification through proper portfolio selection process and everyone tries to optimize their returns given a certain level of risk. In order to do so they are using different statistical measures those have been derived over time to calculate risk. So selection of such method is limited to the understanding of a certain method to a certain investor and their effectiveness of results as compare to other methods.

Assignment得出的結論是，風險更多的是一個主觀術語，不同的分析師和投資者以自己的方式衡量和感知風險。用今天的話來說，即使是一個人也不能低估風險在選擇證券時的重要性，并強調通過適當的投資組合選擇過程實現多樣化，每個人都試圖在一定的風險水平下優化自己的回報。為了做到這一點，他們使用了不同的統計指標來計算風險。因此，與其他方法相比，此類方法的選擇僅限于特定投資者對特定方法的理解及其結果的有效性。本站提供各國各專業留學生assignment代寫或指導服務，如有需要可咨詢本平臺。

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